Xiaowang Chen received his Ph.D. in Mechanical Engineering from University of Science and Technology Beijing in 2018. He is now a Lecturer at the School of Mechanical Engineering at the University of Science and Technology Beijing. His research interests include Condition Monitoring and Fault Diagnosis of Machinery, as well as Signal Processing Methods. He has undertaken 1 China Postdoctoral Science Foundation funded project, and 1 Fundamental Research Funds for the Central Universities. He has published over 10 peer-reviewed papers on machinery fault diagnosis and signal processing. 

Academic Qualification

Sep. 2009 – Jun. 2013, BSc, Vehicle Engineering, University of Science and Technology Beijing

Sep. 2013 – Jun. 2018, PhD, Mechanical Engineering, University of Science and Technology Beijing

Occupational carreer starting from Graduation

Aug. 2018 – Lecturer, School of Mechanical Engineering, University of Science and Technology Beijing

Research interests

- Condition Monitoring and Fault Diagnosis of Machinery

- Signal Processing

Selected Publications

[1]Xiaowang Chen and Zhipeng Feng, Induction motor stator current analysis for planetary gearbox fault diagnosis under time-varying speed conditions, Mechanical Systems and Signal Processing, 140 (2020) 106691

[2]Xiaowang Chen and Zhipeng Feng, Time-frequency space vector modulus analysis of motor current for planetary gearbox fault diagnosis under variable speed conditions, Mechanical Systems and Signal Processing, 121 (2019) 636-654

[3]Xiaowang Chen and Zhipeng Feng, Iterative generalized time-frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions, Mechanical Systems and Signal Processing, 80 (2016) 429-444

[4]Zhipeng Feng, Xiaowang Chen and Ming Liang, Iterative generalized synchrosqueezing transform for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions, Mechanical Systems and Signal Processing, 52-53 (2015) 360-375

[5]Zhipeng Feng, Xiaowang Chen and Ming J. Zuo, Induction motor stator current AM-FM model and demodulation analysis for planetary gearbox fault diagnosis, IEEE Transactions on Industrial Informatics, 15 (2019) 2386-2394